# Loss Given Default (LGD) ## What is loss on default (LGD)?

Loss on Default (LGD) is the amount of money a bank or other financial institution loses when a borrower defaults on a loan, represented as a percentage of total exposure at the time of default. The total LGD of a financial institution is calculated after a review of all outstanding loans using accumulated losses and exposure.

### Key points to remember

• Loss on Default (LGD) is an important calculation for financial institutions that project their expected losses due to borrowers defaulting on loans.
• The expected loss on a given loan is calculated by multiplying the LGD by the probability of default and the exposure to default.
• An important figure for any financial institution is the cumulative amount of expected losses on all outstanding loans.

## Understanding the loss in the event of default (LGD)

Banks and other financial institutions determine credit losses by analyzing actual defaults. Quantifying losses can be complex and require analysis of several variables. An analyst takes these variables into account when examining all loans issued by the bank to determine the LGD. How credit losses are recognized in a company’s financial statements includes determining a provision for credit losses and an allowance for doubtful accounts.

For example, consider that bank A lends \$ 2 million to company XYZ and that company is defaulting. Bank A’s loss is not necessarily \$ 2 million. Other factors should be taken into account, such as the amount of assets the bank can hold as collateral, if installments have already been made to reduce the outstanding balance, and if the bank uses the justice system to repair the loan. company XYZ. Considering these and other factors, Bank A may, in reality, have suffered a much smaller loss than the original loan of \$ 2 million.

Determining the amount of losses is an important and fairly common parameter in most risk models. The LGD is an essential component of the Basel model (Basel II), a set of international banking regulations, as it is used in the calculation of economic capital, expected loss and regulatory capital. The expected loss is calculated as the LGD of a loan multiplied by its probability of default (PD) and the exposure of the financial institution in the event of default (EAD).

Although there are a number of ways to calculate the LGD, the raw calculation is most appreciated by many analysts and accountants. The reason is largely because of its simple formula, which does not take into account the value of the collateral on the loan. This LGD calculation compares the dollar amount of the potential or actual loss to the total amount of the exposure at the time a loan is in default. This method is also the most popular, as academic analysts generally only have access to bond market data, which means that collateral values ​​are not available, unknown, or unimportant.

The most popular method among accountants and analysts to determine the LGD is the gross calculation, which does not involve the value of the collateral on the loan.

## Example of loss in the event of default

Imagine that a borrower takes out a loan of \$ 400,000 for a condo. After making installments on the loan for a few years, the borrower faces financial difficulties and defaults when the loan has an outstanding balance or a default exposure of \$ 300,000. The bank seized the condo and was able to sell it for \$ 240,000. The net loss to the bank is \$ 60,000 (\$ 300,000 – \$ 240,000) and the LGD is 20% (\$ 300,000 – \$ 240,000) / \$ 300,000).

In this scenario, the expected loss would be calculated by the following equation: LGD (20%) X probability of default (100%) X exposure to default (\$ 300,000) = \$ 60,000. If the financial institution anticipated a potential but not certain loss, the expected loss would be different. Using the same figures as in the above scenario, but assuming only a 50% probability of default, the equation for calculating the expected loss is: LGD (20%) X probability of default (50%) X default exposure (\$ 300,000) = \$ 30,000.